{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stable Diffusion Tutorial\n",
    "\n",
    "HuggingFace's `diffuser` is a python package for fast experimentation with diffusion models. Let's install it and get started!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: diffusers[torch] in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (0.18.1)\n",
      "Requirement already satisfied: huggingface-hub>=0.13.2 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from diffusers[torch]) (0.16.4)\n",
      "Requirement already satisfied: importlib-metadata in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from diffusers[torch]) (6.0.0)\n",
      "Requirement already satisfied: filelock in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from diffusers[torch]) (3.9.0)\n",
      "Requirement already satisfied: numpy in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from diffusers[torch]) (1.24.2)\n",
      "Requirement already satisfied: requests in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from diffusers[torch]) (2.28.2)\n",
      "Requirement already satisfied: Pillow in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from diffusers[torch]) (9.4.0)\n",
      "Requirement already satisfied: regex!=2019.12.17 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from diffusers[torch]) (2022.10.31)\n",
      "Requirement already satisfied: torch>=1.4 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from diffusers[torch]) (2.0.1)\n",
      "Requirement already satisfied: accelerate>=0.11.0 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from diffusers[torch]) (0.17.0.dev0)\n",
      "Requirement already satisfied: psutil in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from accelerate>=0.11.0->diffusers[torch]) (5.9.4)\n",
      "Requirement already satisfied: packaging>=20.0 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from accelerate>=0.11.0->diffusers[torch]) (23.0)\n",
      "Requirement already satisfied: pyyaml in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from accelerate>=0.11.0->diffusers[torch]) (6.0)\n",
      "Requirement already satisfied: fsspec in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from huggingface-hub>=0.13.2->diffusers[torch]) (2023.6.0)\n",
      "Requirement already satisfied: tqdm>=4.42.1 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from huggingface-hub>=0.13.2->diffusers[torch]) (4.65.0)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from huggingface-hub>=0.13.2->diffusers[torch]) (4.5.0)\n",
      "Requirement already satisfied: nvidia-cufft-cu11==10.9.0.58 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (10.9.0.58)\n",
      "Requirement already satisfied: nvidia-cusparse-cu11==11.7.4.91 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (11.7.4.91)\n",
      "Requirement already satisfied: networkx in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (3.1)\n",
      "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (11.7.99)\n",
      "Requirement already satisfied: nvidia-cuda-cupti-cu11==11.7.101 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (11.7.101)\n",
      "Requirement already satisfied: jinja2 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (3.1.2)\n",
      "Requirement already satisfied: nvidia-nccl-cu11==2.14.3 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (2.14.3)\n",
      "Requirement already satisfied: triton==2.0.0 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (2.0.0)\n",
      "Requirement already satisfied: nvidia-curand-cu11==10.2.10.91 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (10.2.10.91)\n",
      "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (8.5.0.96)\n",
      "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (11.7.99)\n",
      "Requirement already satisfied: sympy in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (1.12)\n",
      "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (11.10.3.66)\n",
      "Requirement already satisfied: nvidia-nvtx-cu11==11.7.91 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (11.7.91)\n",
      "Requirement already satisfied: nvidia-cusolver-cu11==11.4.0.1 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from torch>=1.4->diffusers[torch]) (11.4.0.1)\n",
      "Requirement already satisfied: setuptools in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.4->diffusers[torch]) (67.5.1)\n",
      "Requirement already satisfied: wheel in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.4->diffusers[torch]) (0.38.4)\n",
      "Requirement already satisfied: cmake in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from triton==2.0.0->torch>=1.4->diffusers[torch]) (3.25.2)\n",
      "Requirement already satisfied: lit in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from triton==2.0.0->torch>=1.4->diffusers[torch]) (15.0.7)\n",
      "Requirement already satisfied: zipp>=0.5 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from importlib-metadata->diffusers[torch]) (3.15.0)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from requests->diffusers[torch]) (3.4)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from requests->diffusers[torch]) (3.1.0)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from requests->diffusers[torch]) (2022.12.7)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from requests->diffusers[torch]) (1.26.14)\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from jinja2->torch>=1.4->diffusers[torch]) (2.1.2)\n",
      "Requirement already satisfied: mpmath>=0.19 in /home/rowel/anaconda3/envs/diffusion/lib/python3.10/site-packages (from sympy->torch>=1.4->diffusers[torch]) (1.3.0)\n"
     ]
    }
   ],
   "source": [
    "! pip install --upgrade diffusers[torch]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Diffuser Pipeline\n",
    "\n",
    "The easiest way to use `diffuser` is through the `DiffuserPipeline` class. This class wraps a `diffuser` model and provides a simple interface for sampling from a pre-trained model. Let's start by importing the class and creating a pipeline.\n",
    "\n",
    "In this example,  the pipeline already contains a `UNet2DModel` model and a `DDPMScheduler`. \n",
    "\n",
    "```python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5752bad9417e4dfdbf79be0b250bc4c2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/25 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=256x256>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from diffusers import DDPMPipeline\n",
    "\n",
    "ddpm = DDPMPipeline.from_pretrained(\"google/ddpm-cat-256\").to(\"cuda\")\n",
    "image = ddpm(num_inference_steps=25).images[0]\n",
    "image"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Decomposing the Diffuser Pipeline\n",
    "\n",
    "Alternatively, the pipeline can be decomposed into its components, a scheduler and a model. This is useful for more advanced use cases, such as training a model from scratch or using a custom scheduler.\n",
    "\n",
    "```python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([960, 920, 880, 840, 800, 760, 720, 680, 640, 600, 560, 520, 480, 440,\n",
       "        400, 360, 320, 280, 240, 200, 160, 120,  80,  40,   0])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from diffusers import DDPMScheduler, UNet2DModel\n",
    "\n",
    "scheduler = DDPMScheduler.from_pretrained(\"google/ddpm-cat-256\")\n",
    "model = UNet2DModel.from_pretrained(\"google/ddpm-cat-256\").to(\"cuda\")\n",
    "scheduler.set_timesteps(25)\n",
    "scheduler.timesteps"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Inference from noise\n",
    "\n",
    "Now that we have a pipeline, we can sample from it. Let's start by sampling from noise.\n",
    "\n",
    "```python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([1, 3, 256, 256])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "\n",
    "sample_size = model.config.sample_size\n",
    "noise = torch.randn((1, 3, sample_size, sample_size)).to(\"cuda\")\n",
    "noise.shape"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### From noise to image\n",
    "\n",
    "Starting with noise, at each timestep, the model predicts the noise residual and the scheduler uses it to predict a less noisy image. The pipeline repeats this process until it reaches the end of the specified number of inference steps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "input = noise\n",
    "\n",
    "for t in scheduler.timesteps:\n",
    "    with torch.no_grad():\n",
    "        noisy_residual = model(input, t).sample\n",
    "    previous_noisy_sample = scheduler.step(noisy_residual, t, input).prev_sample\n",
    "    input = previous_noisy_sample"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing the output image\n",
    "\n",
    "Let's visualize the output image using Pillow.\n",
    "\n",
    "```python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=256x256>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from PIL import Image\n",
    "import numpy as np\n",
    "\n",
    "image = (input / 2 + 0.5).clamp(0, 1)\n",
    "image = image.cpu().permute(0, 2, 3, 1).numpy()[0]\n",
    "image = Image.fromarray((image * 255).round().astype(\"uint8\"))\n",
    "image"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "diffusion",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
